J
Junsuk Rho
Researcher at Pohang University of Science and Technology
Publications - 333
Citations - 13493
Junsuk Rho is an academic researcher from Pohang University of Science and Technology. The author has contributed to research in topics: Metamaterial & Medicine. The author has an hindex of 41, co-authored 236 publications receiving 7173 citations. Previous affiliations of Junsuk Rho include Yonsei University & University of Lahore.
Papers
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Journal ArticleDOI
Focus-Tunable Planar Lenses by Controlled Carriers over Exciton
Sehong Park,Chaebin Park,Yun Ji Hwang,Jeongseob Kang,Gilho Lee,Youngho Seo,Young Tea Chun,Young Tea Chun,Junsuk Rho,Junsuk Rho,Jong Min Kim,James Hone,Seong Chan Jun +12 more
Journal ArticleDOI
High numerical aperture RGB achromatic metalens in the visible
Sang Hun Baek,Juhoon Kim,Ye-Hoon Kim,Won Seok Cho,Trevon Badloe,Seong-Won Moon,Junsuk Rho,Jong-Lam Lee +7 more
TL;DR: In this paper , the authors theoretically and experimentally demonstrate an RGB achromatic metalens that operates concurrently at three visible wavelengths (i.e., 450, 532, and 700 nm) with a high numerical aperture of 0.87.
Journal ArticleDOI
Planar Optical Cavities Hybridized with Low‐Dimensional Light‐Emitting Materials
TL;DR: In this article , the integration of low-dimensional light-emitting materials and planar optical resonators is discussed. But, the authors do not consider the effect of cavities on the performance of the integrated system and instead focus on the physics of cavity-emitter interactions.
Proceedings ArticleDOI
Helicity-Multiplexed Hologram via All-Dielectric Metasurface in the Visible Domain
Muhammad Afnan Ansari,Muhammad Qasim Mehmood,Muhammad Hamza Waseem,Inki Kim,Nasir Mahmood,Tauseef Tauqeer,Selcuk Yerci,Junsuk Rho +7 more
TL;DR: In this article, a transmission type helicity-multiplexed metasurface hologram is demonstrated at wavelength of 633 nm using low loss hydrogenated amorphous silicon to achieve the pragmatic features of meetingasurfaces in the integrated photonic circuits.
Journal ArticleDOI
Deep learning for topological photonics
TL;DR: In this paper , the authors review the specific field that combines topological photonics and deep learning (DL) and discuss recent studies of DL applications to topological systems using neural network (NN) algorithms.